Shale gas geological dessert post-stack earthquake prediction method and system based on rock physical quantity edition and program product
By combining rock physical quantification analysis and post-stack seismic inversion, the problem of multiple solutions in shale gas geological sweet spots was solved, and high-precision distribution prediction was achieved.
Patent Information
- Application Number
- CN202411061708.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-08-05
- Publication Date
- 2026-02-06
AI Technical Summary
Existing technologies are insufficient to effectively address the ambiguity of geological sweet spots in shale gas, and the accuracy of predicting shale TOC and porosity directly using seismic data is difficult to guarantee.
By analyzing rock physical scales and utilizing the intrinsic relationship between core samples and well logging parameters, a rock physical scale is established, which is then combined with post-stack seismic inversion to predict the planar distribution of shale gas geological sweet spots.
It effectively solves the problem of multiple solutions in seismic data prediction and improves the accuracy and consistency of shale gas geological sweet spot distribution prediction.
Smart Images
Figure CN121477286A_ABST
Abstract
Description
Technical Field
[0001] This application pertains to the field of shale oil and gas and tight oil and gas exploration, and particularly relates to a method, system and program product for post-stack seismic prediction of shale gas geological sweet spots based on rock physical quantification. Background Technology
[0002] Domestic and international exploration practices show that the key to shale gas exploration is identifying high-yield sweet spots. These "sweet spots" are mainly characterized by the following aspects: large shale thickness, shale located within a "gas window," high total organic carbon (TOC) content, and high porosity. Shale exhibits high content of brittle minerals such as silica and quartz (high compressibility), and displays overpressure and gas anomalies. High organic carbon (TOC) content and high porosity are particularly noteworthy as they reflect the two soft components of shale and are considered crucial parameters for predicting shale gas geological sweet spots. Quantitative characterization of these geophysical parameters is therefore essential. Previously, seismic inversion and seismic attribute methods were used directly from seismic data to characterize shale TOC content and porosity separately. The overlapping areas were then identified as shale gas geological sweet spot distribution regions. In the early stages of exploration, due to a lack of shale core samples, direct prediction of shale TOC content and porosity using seismic data was often employed. However, this method suffers from high ambiguity and difficulty in guaranteeing prediction accuracy.
[0003] To address this issue, it is necessary to provide a post-stack seismic prediction method, system, and program product for shale gas geological sweet spots based on rock physical quantification. This would solve the problem of multiple solutions arising from directly using post-stack seismic data to predict TOC and porosity in shale, and further expand the shale gas geological sweet spot prediction method based on rock physical quantification constraints, providing a new technical means for predicting the distribution of shale gas geological sweet spots. Summary of the Invention
[0004] To overcome the shortcomings of the existing technology, this application conducts rock physical analysis on shale core samples to identify the logging response characteristics that affect the changes in TOC content and porosity of shale, thereby establishing a rock physical scale based on experimental analysis of shale core samples. Then, post-stack inversion based on the constraints of the rock physical scale is carried out to directly predict the planar distribution of shale gas geological sweet spots.
[0005] The first objective of this application is to provide a method for predicting post-stack earthquakes in shale gas geological sweet spots based on rock physical quantification, including:
[0006] The rock physical sensitive parameters of the geological sweet spots of shale gas in the study area were analyzed;
[0007] A rock physical scale for the geological sweet spot of shale gas in the study area was established based on the analysis of rock physical sensitive parameters.
[0008] Based on rock physics quantification, post-stack seismic inversion was used to predict the planar distribution of shale gas geological sweet spots in the study area.
[0009] Furthermore, the rock physical sensitive parameters of the shale gas geological sweet spots in the study area were analyzed, including:
[0010] Experimental analysis and testing of total organic carbon content, P-wave velocity, and porosity were conducted on marine shale core samples from the study area. Vertical distribution maps of measured total organic carbon content, measured P-wave velocity, and measured porosity were established for the marine shale development zones.
[0011] Based on the vertical distribution maps of measured total organic carbon content, measured longitudinal wave velocity, and measured porosity, we conducted an interpolation analysis of measured total organic carbon content with measured longitudinal wave velocity, and measured porosity with measured longitudinal wave velocity.
[0012] Furthermore, based on the analysis of rock-physical sensitive parameters, a rock-physical quantification of shale gas geological sweet spots is established, including:
[0013] The geological sweet spots and P-wave velocities of marine shale gas in the study area were statistically analyzed in the same rock physical scale with those of typical marine shale gas geological sweet spots and P-wave velocities. This yielded a quantitative relationship between the geological sweet spots and P-wave velocities of shale gas in the study area, and established a rock physical scale for the P-wave velocity and geological sweet spots of shale gas in the study area.
[0014] Furthermore, the quantitative relationship is as follows:
[0015]
[0016] Among them, V p The P-wave velocity of the shale in the study area is given by , and TOC represents the total organic carbon content of the shale in the study area. The porosity of the shale in the study area.
[0017] Furthermore, based on rock physics quanta, post-stack seismic inversion was used to predict the planar distribution of shale gas geological sweet spots in the study area, including:
[0018] Post-stack seismic P-wave velocity inversion was carried out under the constraints of shale P-wave velocity and petrophysical quantities of geological sweet spots in the study area to obtain the inverted P-wave velocity;
[0019] The initial inverted P-wave velocity is matched with the P-wave velocity calculated from actual well logging in the study area until the preset matching degree is achieved.
[0020] The matched inverted P-wave velocities were converted into a planar distribution map of P-wave velocities in the study area using the stratigraphic slicing technique.
[0021] By combining the planar distribution map of P-wave velocity in the study area with the quantitative relationship between the geological sweet spots of shale gas in the study area and P-wave velocity, a planar distribution map of geological sweet spots of shale gas in the study area was obtained.
[0022] Furthermore, the preset matching degree is 0.7.
[0023] The second objective of this application is to provide a post-stack seismic prediction system for shale gas geological sweet spots based on rock physical quantities, including:
[0024] The analysis module is used to analyze the rock physical sensitive parameters of the shale gas geological sweet spots in the study area;
[0025] The model building module is used to build rock physical models of the geological sweet spots of shale gas in the study area based on the analysis of rock physical sensitive parameters;
[0026] The prediction module is used to predict the planar distribution of shale gas geological sweet spots in the study area based on post-stack seismic inversion using rock physics quanta.
[0027] A third objective of this application is to provide an electronic device, including a memory and a processor, wherein the memory stores a computer program or instructions, and when the computer program or instructions are executed by the processor, they are used to at least implement the methods described above.
[0028] The fourth objective of this application is to provide a computer-readable storage medium storing a computer program or instructions that, when executed by a processor, are at least used to implement the methods described above.
[0029] The fifth objective of this application is to provide a computer program product stored in a computer-readable storage medium, which, when executed by a processor, is used to implement at least the above-described method.
[0030] The technical effects and advantages of this application are as follows:
[0031] 1. This application innovatively combines the petrographic data of shale samples with post-stack seismic data, and utilizes the intrinsic relationship between core samples and well logging parameters to conduct research on shale TOC, With Shale V p Well logging characteristic analysis to establish shale geological sweet spots The rock physical scale was used to predict the planar distribution of shale geological sweet spots by conducting post-stack seismic inversion under the constraints of the rock physical scale, thus solving the problem of directly predicting shale TOC using seismic data. The distribution of geological sweet spots in shale gas has multiple interpretations, which effectively predicted the planar distribution characteristics of geological sweet spots in shale gas.
[0032] 2. The method of this application has achieved good application results in exploration practice. At present, the planar distribution of shale gas geological sweet spots predicted by this technology has a high degree of agreement with the actual drilling.
[0033] Other features and advantages of this application will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the application. The objectives and other advantages of this application may be realized and obtained by means of the structures pointed out in the description, claims and drawings. Attached Figure Description
[0034] Figure 1 This is a flowchart of a post-stack seismic prediction method for shale gas geological sweet spots based on rock physical quantities, as proposed in this application.
[0035] Figure 2 Vertical distribution diagram of measured total organic carbon content, measured P-wave velocity, and measured porosity in the shale development section of well A in the study area;
[0036] Figure 3 A plot showing the intersection of measured P-wave velocity and measured total organic carbon content in the shale of the study area;
[0037] Figure 4 A plot showing the intersection of measured P-wave velocity and measured porosity in the shale of the study area;
[0038] Figure 5 A rock physical scale for P-wave velocity and geological sweet spots in the shale of the study area;
[0039] Figure 6 The inversion profile of the east-west longitudinal wave velocity through well A in the study area;
[0040] Figure 7 The inversion profile of the P-wave velocity in the north-south direction through well A in the study area;
[0041] Figure 8 A planar distribution map of P-wave velocity in the shale of the study area;
[0042] Figure 9 This is a planar distribution map of shale gas geological sweet spots in the study area. Detailed Implementation
[0043] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0044] Firstly, such as Figure 1 As shown, this application provides a method for predicting post-stack seismic activity in shale gas geological sweet spots based on rock physical quantities, including:
[0045] The rock physical sensitive parameters of the geological sweet spots of shale gas in the study area were analyzed;
[0046] A rock physical scale for the geological sweet spot of shale gas in the study area was established based on the analysis of rock physical sensitive parameters.
[0047] Based on rock physics quantification, post-stack seismic inversion was used to predict the planar distribution of shale gas geological sweet spots in the study area.
[0048] In some embodiments of this application, rock-physical sensitive parameters of shale gas geological sweet spots in the study area are analyzed, including:
[0049] Experimental analysis and testing of total organic carbon content, P-wave velocity, and porosity were conducted on marine shale core samples from the study area. Vertical distribution maps of measured total organic carbon content, measured P-wave velocity, and measured porosity were established for the marine shale development zones.
[0050] Based on the vertical distribution maps of measured total organic carbon content, measured longitudinal wave velocity, and measured porosity, we conducted an interpolation analysis of measured organic carbon content with measured longitudinal wave velocity, and measured porosity with measured longitudinal wave velocity.
[0051] In some embodiments of this application, a rock physical quantification of shale gas geological sweet spots is established based on the analysis of rock physical sensitive parameters, including:
[0052] The geological sweet spots and P-wave velocities of marine shale gas in the study area were statistically analyzed in the same rock physical scale with those of typical marine shale gas geological sweet spots and P-wave velocities. This yielded a quantitative relationship between the geological sweet spots and P-wave velocities of shale gas in the study area, and established a rock physical scale for the P-wave velocity and geological sweet spots of shale gas in the study area.
[0053] In some embodiments of this application, the quantitative relationship is as follows:
[0054]
[0055] Among them, V p The P-wave velocity of the shale in the study area is given by , and TOC represents the total organic carbon content of the shale in the study area. The porosity of the shale in the study area.
[0056] In some embodiments of this application, the planar distribution of shale gas geological sweet spots in the study area is predicted based on post-stack seismic inversion using rock physics quanta, including:
[0057] Post-stack seismic P-wave velocity inversion was carried out under the constraints of shale P-wave velocity and petrophysical quantities of geological sweet spots in the study area to obtain the inverted P-wave velocity;
[0058] The initial inverted P-wave velocity is matched with the P-wave velocity calculated from the actual well logging until the preset matching degree is achieved.
[0059] The matched inverted P-wave velocities were converted into a planar distribution map of P-wave velocities in the study area using the stratigraphic slicing technique.
[0060] By combining the planar distribution map of P-wave velocity in the study area with the quantitative relationship between the geological sweet spots of shale gas in the study area and P-wave velocity, a planar distribution map of geological sweet spots of shale gas in the study area was obtained.
[0061] In some embodiments of this application, the preset matching degree is 0.7.
[0062] Secondly, this application discloses a post-stack earthquake prediction system for shale gas geological sweet spots based on rock physical quantities, including:
[0063] The analysis module is used to analyze the rock physical sensitive parameters of the shale gas geological sweet spots in the study area;
[0064] The model building module is used to build rock physical models of the geological sweet spots of shale gas in the study area based on the analysis of rock physical sensitive parameters;
[0065] The prediction module is used to predict the planar distribution of shale gas geological sweet spots in the study area based on post-stack seismic inversion using rock physics quanta.
[0066] Thirdly, this application discloses an electronic device, including a memory and a processor. The memory stores a computer program or instructions, which, when executed by the processor, are used to at least implement the aforementioned method.
[0067] Fourthly, this application discloses a computer-readable storage medium storing a computer program or instructions, which, when executed by a processor, are at least used to implement the above-described method.
[0068] Fifthly, this application discloses a computer program product stored in a computer-readable storage medium. When the computer program product is executed by a processor, it is used to implement at least the above-described method.
[0069] To better illustrate this solution, the following embodiments are provided.
[0070] Example
[0071] Step 1: Analyze the rock physical sensitive parameters of the shale gas geological sweet spots in the study area.
[0072] First, core observation and systematic sampling were conducted on the shale-developed section of Well A in the study area. Experimental analysis was performed on the total organic carbon content, P-wave velocity, and porosity of the collected marine shale core samples. Simultaneously, a vertical distribution map of the measured total organic carbon content, measured P-wave velocity, and measured porosity of the marine shale-developed section of Well A was established (e.g., [image of data]). Figure 2 (As shown).
[0073] Furthermore, sensitive petrophysical parameter analyses were conducted on the total organic carbon (TOC) content and porosity of the marine shale development zone in Well A of the study area. Previously, it was believed that the AC and RT curves, i.e., the ΔlgR method, mainly influenced the changes in TOC content in shale. This embodiment, through cross-analysis of measured TOC content and measured P-wave velocity in core samples from the marine shale of Well A in the study area, found a good correlation between TOC content and P-wave velocity in marine shale. Specifically, the P-wave velocity of marine shale with high TOC content tends to decrease. Compared with carbonate rocks developed in the marine shale development zone of the study area, the decrease in P-wave velocity of marine shale in the study area with increasing TOC content is greater (e.g., ...). Figure 3 (As shown). Using the same method, a cross-analysis of measured porosity and measured P-wave velocity was conducted on the marine shale in Well A of the study area. It was also found that the P-wave velocity of the marine shale tends to decrease with increasing porosity. Compared with another type of carbonate rock developed in the marine shale development zone of the study area, the decrease in P-wave velocity of the marine shale in the study area with increasing porosity is greater (e.g., Figure 4 (As shown). Thus, the characteristics of P-wave velocity variation in the rock physical parameters sensitive to shale gas geological sweet spots in the study area were obtained, namely, with the increase of total organic carbon (TOC) and porosity... Increased P-wave velocity V of marine shale in the study area p The trend is decreasing; compared with the shale sections in the study area that develop another type of lithological carbonate rock, the P-wave velocity V of the marine shale is lower. p The decrease was even greater.
[0074] Step 2: Based on the analysis of rock physical sensitive parameters in Step 1, establish a rock physical scale for the geological sweet spot of shale gas in the study area.
[0075] Through step 1, the TOC in the geological sweet spot of shale gas in the study area was analyzed. Analysis of rock physics sensitive parameters of two important soft components clarified the geological sweet spots of marine shale in the study area. Sensitive rock physical parameters—P-wave velocity—were investigated, and further exploration of shale gas geological sweet spots in the study area was conducted. Intersection analysis with P-wave velocity, a rock physics sensitive parameter.
[0076] The geological sweet spots and P-wave velocities of marine shale gas in the study area were statistically analyzed in the same rock physical scale with those of typical marine shale gas geological sweet spots and P-wave velocities. This yielded a quantitative relationship between the geological sweet spots and P-wave velocities of shale gas in the study area, and established a rock physical scale for the P-wave velocity and geological sweet spots of shale gas in the study area.
[0077] By statistically analyzing typical marine shale gas geological sweet spots and P-wave velocities alongside those of the marine shale gas geological sweet spots and P-wave velocities in the study area within the same rock physics module, a quantitative relationship between shale gas geological sweet spots and P-wave velocities in the study area was obtained, establishing... Figure 5 The graph shows the P-wave velocity and geological sweet spot rock physical quantities of shale in the study area. Figure 5 The longitudinal wave velocity V of the shale in the study area was determined. p With geological desserts The quantitative relationship between them, i.e. The correlation between the two is as high as 0.84. From step 1, it can be seen that the marine shale V in the study area... p With TOC, Increase and decrease, i.e., V p With TOC and respectively If there is a negative correlation between them, then V p and The negative correlation still applies in the study area.
[0078] Step 3: Based on rock physics quanta, conduct post-stack seismic inversion to predict the planar distribution of shale gas geological sweet spots in the study area.
[0079] First, post-stack seismic inversion was conducted under the constraints of shale P-wave velocity and geological sweet spot petrophysical quantities in the study area. The inversion results were calculated using V from well logging data from actual well A. p Verification, up to V obtained from post-stack seismic inversion. p V calculated from the actual drilling well A p The fit must reach 0.7 or higher. Figure 6 This is an inversion profile of the post-stack seismic P-wave velocity in the east-west direction through well A in the study area. Figure 7 This is a post-stack seismic P-wave velocity inversion profile in the north-south direction through well A in the study area. Figure 6 and Figure 7 The logging curve near well A is a P-wave velocity curve. From Figure 6 and Figure 7 It can be seen that the V calculated by post-stack seismic inversion p The agreement with the Vp calculated from the actual drilling well A is good. Subsequently, the Vp calculated from the post-stack seismic inversion was further analyzed using the inter-stratigraphic slicing technique. p The study area V can be obtained by processing the data. p Planar distribution diagram of velocity (e.g.) Figure 8 (As shown).
[0080] Then, in study area V p Based on the planar distribution map of velocity, combined with the geological sweet spots of marine shale Vp and shale gas in the study area obtained in step 2, The quantitative relationship can be transformed into a formula to obtain the geological sweet spot of shale gas in the study area. Planar distribution map (e.g.) Figure 9 (As shown).
[0081] In summary, this application innovatively combines the petrographic data of shale samples with post-stack seismic data, and utilizes the intrinsic relationship between core samples and well logging parameters to conduct research on shale TOC, With Shale V p Well logging characteristic analysis to establish shale geological sweet spots The rock physical scale was used to predict the planar distribution of shale geological sweet spots by conducting post-stack seismic inversion under the constraints of the rock physical scale, thus solving the problem of directly predicting shale TOC using seismic data. The distribution of geological sweet spots in shale gas has problems such as multiple interpretations, which can effectively predict the planar distribution characteristics of geological sweet spots in shale gas.
[0082] Finally, it should be noted that the above description is only a preferred embodiment of this application and is not intended to limit this application. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.
Claims
1. A shale gas geology sweet spot post-stack seismic prediction method based on rock physics volume version, characterized in that, The method comprises the following steps: analyzing rock physical sensitive parameters of shale gas geology sweet spots in the study area; establishing a rock physical quantity version of the shale gas geology sweet spots in the study area based on the analysis of the rock physical sensitive parameters; predicting the planar distribution of the shale gas geology sweet spots in the study area by post-stack seismic inversion based on the rock physical quantity version.
2. The rock physics volume-based shale gas geology sweet spot post-stack seismic prediction method according to claim 1, characterized in that, The analysis of the rock physical sensitive parameters of the shale gas geology sweet spots in the study area comprises: performing experimental analysis and testing of the organic carbon content, the P-wave velocity and the porosity of the marine shale core samples in the study area, and establishing a vertical distribution map of the measured organic carbon content, the measured P-wave velocity and the measured porosity of the marine shale development layer; performing intersection analysis of the measured organic carbon content and the measured P-wave velocity, and the measured porosity and the measured P-wave velocity based on the vertical distribution map of the measured organic carbon content, the measured P-wave velocity and the measured porosity.
3. The rock physics volume-based shale gas geology sweet spot post-stack seismic prediction method according to claim 2, characterized in that, The establishment of the rock physical quantity version of the shale gas geology sweet spots based on the analysis of the rock physical sensitive parameters comprises: statistically analyzing the marine shale gas geology sweet spots and the P-wave velocity in the study area and the typical marine shale gas geology sweet spots and the P-wave velocity in the same rock physical quantity version, obtaining a quantitative relationship between the shale gas geology sweet spots and the P-wave velocity in the study area, and establishing a rock physical quantity version of the shale P-wave velocity and the geology sweet spot in the study area.
4. The rock physics volume-based shale gas geology sweet spot post-stack seismic prediction method of claim 3, wherein, The quantitative relationship is: where V p is the longitudinal wave velocity of the shale in the study area, TOC is the total organic carbon content of the shale in the study area, is the porosity of the shale in the study area.
5. The rock physics volume-based shale gas geology sweet spot post-stack seismic prediction method of claim 3, wherein, The prediction of the planar distribution of the shale gas geology sweet spots in the study area by post-stack seismic inversion based on the rock physical quantity version comprises: performing post-stack seismic P-wave velocity inversion under the constraint of the rock physical quantity version of the shale P-wave velocity and the geology sweet spot in the study area to obtain an inverted P-wave velocity; matching the inverted P-wave velocity with the P-wave velocity calculated by the actual logging in the study area until a preset matching degree is reached; converting the matched inverted P-wave velocity into a planar distribution map of the P-wave velocity in the study area by layer sectioning technology; obtaining a planar distribution map of the shale gas geology sweet spots in the study area by using the planar distribution map of the P-wave velocity in the study area in combination with the quantitative relationship between the shale gas geology sweet spots and the P-wave velocity in the study area.
6. The rock physics volume-based shale gas geology sweet spot post-stack seismic prediction method according to claim 5, characterized in that, The preset matching degree is 0.
7.
7. A rock physics volume based shale gas geology sweet spot post stack seismic prediction system characterized by, The method comprises the following steps: analyzing rock physical sensitive parameters of shale gas geology sweet spots in the study area; establishing a rock physical quantity version of the shale gas geology sweet spots in the study area based on the analysis of the rock physical sensitive parameters; predicting the planar distribution of the shale gas geology sweet spots in the study area by post-stack seismic inversion based on the rock physical quantity version.
8. An electronic device comprising a memory and a processor, characterized in that The memory stores computer programs or instructions, which are executed by the processor to at least implement the method in any one of claims 1-6.
9. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer programs or instructions, which are executed by the processor to at least implement the method in any one of claims 1-6.
10. A computer program product stored in a computer readable storage medium, characterized in that, The computer program product is executed by the processor to at least implement the method in any one of claims 1-6.